The broad goal of this research project is to identify patterns of driving performance associated with age-related cognitive decline. This project to date has disclosed several novel relationships between cognitive abilities such as attention, decision-making and memory in older drivers, and their driving performance, patterns of safety errors, and susceptibility to crashes. Guided by our findings thus far, the next phase of this project addresses several specific aims to: (1) obtain a comprehensive longitudinal picture of age-related changes in older driver abilities by following a cohort of 120 drivers over age 65, most of whom are currently enrolled in this project;(2) study a particularly high-risk group of 100 older drivers over age 65 who had their licenses suspended and reinstated (n = 50) or revoked (n = 50) in the past year;(3) determine which cognitive impairments contribute the most to driving errors and crashes and to develop predictive models of driving fitness. A comprehensive battery of neuropsychological and psychophysical measures, an instrumented vehicle, and a state-of-the-art driving simulator will be used to assess a set of cognitive and behavioral variables that may contribute to driver safety errors and crashes. Experimental driving scenarios will address mechanisms underlying side-impact collisions at traffic intersections, collisions with lead or merging vehicles due to inaccurate time-to-contact estimates, and run-off-the-road crashes on curved roads. As an outcome of these studies, we expect to: (1) obtain a more detailed picture of the natural history of driving and cognition in a stable cohort of aging individuals;(2) obtain better chronological evidence on predicting future driving success or failure based on cognitive abilities and demographic factors at any given time;(3) determine which cognitive impairments contribute the most to specific driving safety errors and crash types in different at-risk groups of older drivers. Identifying reliable and valid cognitive and driving performance measures for predicting driving safety errors and crashes will advance driver risk assessment, mitigate vehicle crashes and injuries caused by cognitively impaired drivers, and protect the mobility and social independence of elderly drivers who do not pose undue safety risks.